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MAKING
DATA-DRIVING
DECISIONS
The Data Revolution is in full swing, transforming everything from
our daily lives to how we do business. The world has watched
in awe as the organizations that are willing, ready, and able to
take on the challenge of harnessing the power of data science
to make predictions about their customers, the market, and their
organization have stood further and further above their peers.
But many organizations are struggling to unleash this power for
their organizations; progress is stymied by misunderstanding,
poor data strategy, and lack of a common language between
teams. The directive to make data-driven decisions flounders as
teams struggle to understand the fundamental principles of data
science.
SO, WHAT’S THE SOLUTION?
CorpU, in partnership with Foster Provost and Vasant Dhar, are
developing a catalyst that will take your team from unsure and
misinformed to confident, articulate, and eager to move forward
into the opportunities that predictive analytics holds for your
organization. Participants will:
• Align data and business understanding and develop
meaningful solutions to issues such as siloing and
mistranslation.
• Develop a highly functional familiarity with key data mining
concepts, unlocking their ability to communicate with analytics
stakeholders.
• Demystify the data science process, allowing them to
productively engage with industry operations.
• Construct a data proposal that will then be crowd-sourced
via Idea Tournament to evaluate, hone, and provide to your
organization for implementation.
• Collaborate to unpack your organization’s current data
strategy and propel your organization into new levels of data
maturity.
Join us in exploring the groundbreaking possibilities
of predictive analytics with real-life case studies, a
course-long simulation full of twists and turns,
collaborative problem solving, and world-class faculty:
Module 1
Introduction to Predictive Analytics: what it is, what it isn’t, and
the potential value for your organization.
Module 2
The Data Mining Process: discover the industry standard data
mining technique and unlock it to begin writing a Data Proposal
for your organization.
Module 3
Introduction to Modeling: demystify the modeling process so
that you can engage productively with analytic teams and/or
consultants.
flexible break (1-3 weeks): conduct data preparation
conversations within your organization
Module 4
Evaluating and Deploying Your Predictions: learn to evaluate
model performance by keeping business understanding at the
forefront.
Module 5:
Leveraging Predictive Analytics for Competitive Advantage:
unpack the need for cross-functional data strategies in order to
develop sustainable competitive advantage.
Module 6:
Idea Tournament: each participant submits a cumulative
data proposal and estimates the value that realized
approach to data could bring to your organization.
Proposals are evaluated by the cohort in order to select and
further hone 2-4 of the most viable opportunities.
About the Faculty
FOSTER PROVOST is Professor of Information Systems and Andre Meyer Faculty Fellow at New York
University’s Stern School of Business. Professor Provost studies data mining, machine learning, social
network analysis and their alignment with business problems. He is also co-author of the guiding text
for this course, Data Science for Business. He has won several awards, including the 2009 INFORMS
Design Science award for social network-based marketing, IBM Faculty Awards for outstanding
research in data mining and machine learning, and a President’s Award from NYNEX Science and
Technology. Professor Provost recently retired as Editor-in-Chief of the journal Machine Learning after
6+ years. He is a member of the editorial boards of the Journal of Machine Learning Research(JMLR)
and the journal Data Mining and Knowledge Discover. He was elected as a founding board member of
the International Machine Learning Society.
VASANT DHAR is a professor at NYU’s Stern School of Business and Co-Director of the Center for
Business Analytics. In addition to serving as Editor in Chief of the journal Big Data, he has written
over 70 research articles, funded by grants from industry and the National Science Foundation. He
pioneered the use of machine learning for predictive modeling on Wall Street across proprietary
systematic trading, risk management, and customer and sales force management. He is a frequent
speaker in academic as well as industrial forums.
Guiding Course Text
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business
introduces the fundamental principles of data science, and walks you through the "data-analytic thinking"
necessary for extracting useful knowledge and business value from the data you collect. This guide also
helps you understand the many data-mining techniques in use today.
Data Science for Business was named by Fortune magazine as one of the top five books for required
reading by an MBA student.